Results 121 to 130 of about 377,814 (287)

Convergence Analysis of Kernel Learning FBSDE Filter

open access: yesCommunications in Mathematical Research
Kernel learning forward backward SDE filter is an iterative and adaptive meshfree approach to solve the nonlinear filtering problem. It builds from forward backward SDE for Fokker-Planker equation, which defines evolving density for the state variable, and employs KDE to approximate density.
Lyu, Yunzheng, Bao, Feng
openaire   +3 more sources

In Situ Study of Resistive Switching in a Nitride‐Based Memristive Device

open access: yesAdvanced Functional Materials, EarlyView.
In situ TEM biasing experiment demonstrates the volatile I‐V characteristic of MIM lamella device. In situ STEM‐EELS Ti L2/L3 ratio maps provide direct evidence of the oxygen vacancies migrations under positive/negative electrical bias, which is critical for revealing the RS mechanism for the MIM lamella device.
Di Zhang   +19 more
wiley   +1 more source

Estimation of 3D facial dynamics with nonlinear filters for position tracking*

open access: yesApplied Mathematics in Science and Engineering
This study presents a comparative evaluation of three nonlinear state estimation filters, the Extended Kalman Filter (EKF), Unscented Kalman Filter (UKF), and Particle Filter (PF), for the task of 3D facial landmark tracking.
Thoa Thieu, Roderick Melnik
doaj   +1 more source

Tailoring Microstructure in Copper‐Based Conductive Metal–Organic Frameworks for Enhanced Chemiresistive Sensing and Uptake of Sulfur Dioxide

open access: yesAdvanced Functional Materials, EarlyView.
Precursor‐ and solvent‐mediated synthesis yields four Cu3(HHTP)2 morphologies with distinct physicochemical, sorption, and sensing properties toward SO2. Uptake capacities correlate with BET surface area, while sensing performance scales with particle aspect ratio.
Patrick Damacet   +5 more
wiley   +1 more source

Convergence Performance of Adaptive Algorithms of L-Filters

open access: yesAdvances in Electrical and Electronic Engineering, 2003
This paper deals with convergence parameters determination of adaptive algorithms, which are used in adaptive L-filters design. Firstly the stability of adaptation process, convergence rate or adaptation time, and behaviour of convergence curve belong ...
Robert Hudec
doaj  

Bimetallic Nanoreactor Activates cGAS‐STING Pathway via mtDNA Release for Cancer Metalloimmunotherapy

open access: yesAdvanced Functional Materials, EarlyView.
A bimetallic Mn–Ca nanoreactor (MCC) is developed as a non‐nucleotide STING nanoagonist for cancer metalloimmunotherapy. MCC induces Ca2+ overload and hydroxyl radical generation, resulting in mitochondrial damage and mtDNA release. The released mtDNA cooperates with Mn2+ to robustly activate cGAS–STING signaling.
Xin Wang Mo   +7 more
wiley   +1 more source

A Family of Variable Step-Size Normalized Subband Adaptive Filter Algorithms Using Statistics of System Impulse Response

open access: yesIranian Journal of Electrical and Electronic Engineering, 2013
This paper presents a new variable step-size normalized subband adaptive filter (VSS-NSAF) algorithm. The proposed algorithm uses the prior knowledge of the system impulse response statistics and the optimal step-size vector is obtained by minimizing the
M. Shams Esfand Abadi, M.S. Shafiee
doaj  

Spectrally Tunable 2D Material‐Based Infrared Photodetectors for Intelligent Optoelectronics

open access: yesAdvanced Functional Materials, EarlyView.
Intelligent optoelectronics through spectral engineering of 2D material‐based infrared photodetectors. Abstract The evolution of intelligent optoelectronic systems is driven by artificial intelligence (AI). However, their practical realization hinges on the ability to dynamically capture and process optical signals across a broad infrared (IR) spectrum.
Junheon Ha   +18 more
wiley   +1 more source

Smarter Sensors Through Machine Learning: Historical Insights and Emerging Trends across Sensor Technologies

open access: yesAdvanced Functional Materials, EarlyView.
This review highlights how machine learning (ML) algorithms are employed to enhance sensor performance, focusing on gas and physical sensors such as haptic and strain devices. By addressing current bottlenecks and enabling simultaneous improvement of multiple metrics, these approaches pave the way toward next‐generation, real‐world sensor applications.
Kichul Lee   +17 more
wiley   +1 more source

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